Findings from a readiness assessment will help determine where to start and how quickly to proceed. Findings can also provide the basis for roadmapping program goals. If there is strong …
Data Quality Program – Implementation Guidelines
Typically, a hybrid approach works best – top-down for sponsorship, consistency, and resources, but bottom-up to discover what is actually broken and to achieve incremental successes. Improving data quality requires …
Data Quality – Audit Code Module and Metrics
Quality Check and Audit Code Modules Create shareable, linkable, and re-usable code modules that execute repeated data quality checks and audit processes that developers can get from a library. If …
Data Quality – Preventive and Corrective Actions
Preventive Actions The best way to create high quality data is to prevent poor quality data from entering an organization. Preventive actions stop known errors from occurring. Inspecting data after …
Data Quality – Tools
Tools should be selected and tool architectures should be set in the.planning phase of the enterprise Data Quality program. Tools provide a.partial rule set starter kit but organizations need to …
Data Quality – Incident Tracking System
The incident tracking system will collect performance data relating to issue resolution, work assignments, volume of issues, frequency of occurrence, as well as the time to respond, diagnose, plan a …
Data Quality – SLA – Service Level Agreements
A data quality Service Level Agreement (SLA) specifies an organization’s expectations for response and remediation for data quality issues in each system. Data quality inspections as scheduled in the SLA …
Data Quality Reporting
The work of assessing the quality of data and managing data issues will not benefit the organization unless the information is shared through reporting so that data consumers understand the …